YangWangHarrisonEtAl2019

Référence

Yang, Y., Wang, H., Harrison, S.P., Prentice, I.C., Wright, I.J., Peng, C., Lin, G. (2019) Quantifying leaf-trait covariation and its controls across climates and biomes. New Phytologist, 221(1):155-168. (Scopus )

Résumé

Plant functional ecology requires the quantification of trait variation and its controls. Field measurements on 483 species at 48 sites across China were used to analyse variation in leaf traits, and assess their predictability. Principal components analysis (PCA) was used to characterize trait variation, redundancy analysis (RDA) to reveal climate effects, and RDA with variance partitioning to estimate separate and overlapping effects of site, climate, life-form and family membership. Four orthogonal dimensions of total trait variation were identified: leaf area (LA), internal-to-ambient CO2 ratio (χ), leaf economics spectrum traits (specific leaf area (SLA) versus leaf dry matter content (LDMC) and nitrogen per area (Narea)), and photosynthetic capacities (Vcmax, Jmax at 25°C). LA and χ covaried with moisture index. Site, climate, life form and family together explained 70% of trait variance. Families accounted for 17%, and climate and families together 29%. LDMC and SLA showed the largest family effects. Independent life-form effects were small. Climate influences trait variation in part by selection for different life forms and families. Trait values derived from climate data via RDA showed substantial predictive power for trait values in the available global data sets. Systematic trait data collection across all climates and biomes is still necessary. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust

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@ARTICLE { YangWangHarrisonEtAl2019,
    AUTHOR = { Yang, Y. and Wang, H. and Harrison, S.P. and Prentice, I.C. and Wright, I.J. and Peng, C. and Lin, G. },
    TITLE = { Quantifying leaf-trait covariation and its controls across climates and biomes },
    JOURNAL = { New Phytologist },
    YEAR = { 2019 },
    VOLUME = { 221 },
    NUMBER = { 1 },
    PAGES = { 155-168 },
    NOTE = { cited By 1 },
    ABSTRACT = { Plant functional ecology requires the quantification of trait variation and its controls. Field measurements on 483 species at 48 sites across China were used to analyse variation in leaf traits, and assess their predictability. Principal components analysis (PCA) was used to characterize trait variation, redundancy analysis (RDA) to reveal climate effects, and RDA with variance partitioning to estimate separate and overlapping effects of site, climate, life-form and family membership. Four orthogonal dimensions of total trait variation were identified: leaf area (LA), internal-to-ambient CO2 ratio (χ), leaf economics spectrum traits (specific leaf area (SLA) versus leaf dry matter content (LDMC) and nitrogen per area (Narea)), and photosynthetic capacities (Vcmax, Jmax at 25°C). LA and χ covaried with moisture index. Site, climate, life form and family together explained 70% of trait variance. Families accounted for 17%, and climate and families together 29%. LDMC and SLA showed the largest family effects. Independent life-form effects were small. Climate influences trait variation in part by selection for different life forms and families. Trait values derived from climate data via RDA showed substantial predictive power for trait values in the available global data sets. Systematic trait data collection across all climates and biomes is still necessary. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust },
    AFFILIATION = { Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China; Joint Center for Global Change Studies (JCGCS), Beijing, 100875, China; State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, College of Forestry, Northwest A&F University, Yangling, Shaanxi 712100, China; School of Archaeology, Geography and Environmental Sciences (SAGES), University of Reading, Reading, RG6 6AH, United Kingdom; AXA Chair of Biosphere and Climate Impacts, Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot, SL5 7PY, United Kingdom; Department of Biological Sciences, Macquarie University, North Ryde, NSW 2109, Australia; Department of Biological Sciences, Institute of Environmental Sciences, University of Quebec at Montreal, C.P. 8888, Succ. Centre-Ville, Montréal, QC H3C 3P8, Canada; Key Laboratory of Stable Isotope and Gulf Ecology, Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong 518055, China },
    AUTHOR_KEYWORDS = { climate; leaf economics spectrum; multivariate analysis; photosynthetic capacity; phylogeny; plant functional traits; vegetation modelling },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1111/nph.15422 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053029859&doi=10.1111%2fnph.15422&partnerID=40&md5=419048b876e0f9db5801d01d96208b1a },
}

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